The present invention relates to carrier aggregation and, more particularly, to secondary component carrier allocation.
Carrier aggregation (CA) is an important feature of LTE-advanced that allows its users to aggregate up to 100 MHz of (dis-)contiguous spectral chunks to provide increased data rates. While the conventional approach of allowing LTE-adv users to be configured on all component carriers, results in maximum diversity gain for scheduling, it also increases the users' power consumption and processing that scale with the number of component carriers. We argue that it is possible to operate the LTE-adv users on a small subset of component carriers to reduce their energy consumption, without any appreciable loss to the scheduling gain. A step in realizing this goal however, is to address the joint problem of component carrier selection as well as scheduling.
We highlight the hardness of the joint problem when the number of component carriers that can be activated for a LTE-adv user is limited. Towards solving the problem, we consider various models that incorporate contiguous/dis-contiguous CA as well as backlogged/finite buffers and propose efficient, greedy algorithms with performance guarantees that are also simple to implement. Our evaluations based on LTE simulation parameters, reveal that our algorithms help realize 80-90% of the maximum scheduling gain with just half the component carriers and provide 15-25% throughput gain over conventional load and signal power (RSRP) based carrier selection schemes.
The conventional approach of allowing LTE-adv users to be configured on all component carriers, results in maximum diversity gain for scheduling. However, it also increases the users' power consumption and processing that scale with the number of component carriers.
The proliferation of mobile devices and the exponential growth of mobile data traffic has increased the demand for higher data rates from next generation cellular networks like LTE-advanced, WiMAX, etc. In addition to OFDMA being employed as the air interface in all these technologies, several other features such as small cells, carrier aggregation, etc. are being considered. While small cells increase the area spectral efficiency and are a key to increasing the system capacity, several challenges remain in realizing them in practice. On the other hand, carrier aggregation provides an immediate, effective solution for network operators to repurpose spectrum from older technologies (eg. 2/3G to 4G) and aggregate fragmented spectral allocations to deliver higher data rates.
Carrier aggregation (CA) can be of multiple types as shown in FIG. 1(a). Component carriers (CC, spectral chunks) can be aggregated dis-contiguously either within a band (intra-band) or across bands (inter-band), but contiguously only within a band (intra-band). While CA is supported only by LTE adv users, LTE-adv (release 10 onwards) itself allows for backward compatibility with release 8/9 users that operate on only one CC. For every user, a CC is configured to be the primary CC (PCC) that is responsible for key operations such as location registration, RRC (re-)establishment, etc. and hence cannot be changed dynamically. On the other hand, the additional CCs (secondary CCs) in CA can be (de-)activated dynamically for LTE-adv users.
In the conventional approach, where LTE-adv users are configured with all available CCs, the selection of CCs is restricted to the choice of PCC for each user, with the remaining CCs serving as SCCs. Due to the nature of operations on PCC, its selection is decoupled from scheduling and determined semi-statically based on load-balancing or reference signal received power (RSRP). While activating LTE-adv users on all CCs provides maximum diversity gain through scheduling, it also increases the energy consumption and processing at the user (device)—factors that scale with the number of CCs activated. Hence, we posit the following question: Is it possible to operate the LTE-adv users on a small subset of component carriers to reduce their energy consumption, without any appreciable loss to the scheduling gain? Given the plethora of network interfaces and applications being housed by smart mobile devices and their consequent impact on battery drainage, understanding the answer to the above question is both important and timely.
We answer in the affirmative and argue that it is indeed possible to operate the LTE-adv users on a small subset of CCs without an appreciable loss to scheduling performance. Note that selection of secondary CCs (SCCs) for LTE adv users now becomes an integral component and directly impacts scheduling performance. Given that SCCs can be (de-)activated dynamically, a key to keeping the loss in performance small, is to integrate and couple CC selection with scheduling and address them jointly for LTE-adv users. Towards addressing this goal and hence seeking an answer to our motivating question, we make the following contributions:                We prove the hardness of the coupled problem of CC selection and scheduling when the number of CCs that can be activated for a LTE-adv user is limited.        Towards solving the problem, we consider various models that incorporate contiguous(C)/dis-contiguous(D) CA as well as backlogged(B)/finite(F) user buffers and propose efficient, greedy algorithms with performance guarantees that are also simple to implement. Specifically, our algorithms yield approximation guarantees of ½, ¼, ½, and ⅓ for the models DB, DF, CB and CF respectively.        Our evaluations based on LTE simulation parameters, reveal that our algorithms help realize 80-90% of the maximum scheduling gain with just half the component carriers and provide 15-25% throughput gain over conventional load-based and RSRP-based carrier selection schemes.        
Our results are promising and indicate that with the help of efficiently designed joint CC selection and scheduling algorithms for LTE-adv users, it is possible to realize close-to the full performance benefits of CA (achieved with all CCs), while expending only a fraction of the user energy.
Existing solutions [1, 2, 3] restrict the number of component carriers for a user by load balancing users on different component carrriers (CCs). However, since the allocation of specific CCs to users is done independent of scheduling, it comes at the expense of diversity gain and throughput performance.